55 resultados para Precipitation forecasting


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This paper describes a simple method to co-precipitate CeO2 and Ce0.8Gd0.2O1.9-delta with ammonium hydroxide from solvents such as: water, ethylene glycol, ethyl alcohol and isopropyl alcohol. Characterization by Raman spectroscopy and XRD evidenced the formation of a solid solution of gadolinium-doped ceria at room temperature. Nanometric particles with crystallite size of 3.1 nm were obtained during synthesis using ethyl alcohol as solvent. This is a promising result compared with those mentioned in the literature, in which the smallest crystallite size reported was, 6.5 nm. (c) 2006 Elsevier B.V. All rights reserved.

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A study of several factors has been carried out in order to determine their influence on rare earth phosphates precipitation from H3PO4 solutions obtained after the treatment of the Kola phosphate rock.

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Experimental data on the precipitation chemistry in the semi-arid savanna of South Africa is presented in this paper. A total of 901 rainwater samples were collected with automatic wet-only samplers at a rural site, Louis Trichardt, and at an industrial site, Amersfoort, from July 1986 to June 1999. The chemical composition of precipitation was analysed for seven inorganic and two organic ions, using ion chromatography. The most abundant ion was SO(4)(2-) and a large proportion of the precipitation is acidic, with 98% of samples at Amersfoort and 94% at Louis Trichardt having a pH below 5.6 ( average pH of 4.4 and 4.9, respectively). This acidity results from a mixture of mineral and organic acids, with mineral acids being the primary contributors to the precipitation acidity in Amersfoort, while at Louis Trichardt, organic and mineral acids contribute equal amounts of acidity. It was found that the composition of rainwater is controlled by five sources: marine, terrigenous, nitrogenous, biomass burning and anthropogenic sources. The relative contributions of these sources at the two sites were calculated. Anthropogenic sources dominate at Amersfoort and biomass burning at Louis Trichardt. Most ions exhibit a seasonal pattern at Louis Trichardt, with the highest concentrations occurring during the austral spring as a result of agricultural activities and biomass combustion, while at Amersfoort it is less pronounced due to the dominance of relatively constant industrial emissions. The results are compared to observations from other African regions.

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The chemical composition, as well as the sources contributing to rainwater chemistry have been determined at Skukuza, in the Kruger National Park, South Africa. Major inorganic and organic ions were determined in 93 rainwater samples collected using an automated wet-only sampler from July 1999 to June 2002. The results indicate that the rain is acidic and the averaged precipitation pH was 4.72. This acidity results from a mixture of mineral acids (82%, of which 50% is H2SO4) and organic acids (18%). Most of the H2SO4 component can be attributed to the emissions of sulphur dioxide from the industrial region on the Highveld. The wet deposition of S and N is 5.9 kgS.ha(-1).yr(-1) and 2.8 kgN.ha(-1).yr(-1), respectively. The N deposition was mainly in the form of NH4+. Terrigenous, sea salt component, nitrogenous and anthropogenic pollutants have been identified as potential sources of chemical components in rainwater. The results are compared to observations from other African regions.

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Aluminium Hydroxides were precipitated from Aluminium Nitrate and Ammonium Hydroxide, at the temperatures 64 degrees C (hot) and 25 degrees C (cold), under the pH conditions 5, 7 and 9. The samples were characterized by X-Ray Diffraction (XRD) and Differential Thermal Analysis (DTA). The hydroxide precipitated at pH 9 and 64 degrees C is built up by pseudoboehmite and a minor share of others apparently amorphous hydroxides. The crystallinity of the hot yielded pseudoboehmite diminishes with the pH. The crystallite size was evaluated as about 40 Angstrom for the best crystallized sample. The cold precipitated product is apparently composed by amorphous or very poorly crystallized hydroxides. Upon heating, the cold precipitated hydroxides, and the low pH and hot precipitated hydroxide, release their structural water before the occurrence, about 430 degrees C, of the transition of the pseudoboehmite to gamma-alumina, and exhibit a shifting (towards low temperature side) and a broadening in the peak of the transition to alpha-alumina, which occurs at 1200 degrees C in the pseudoboehmite pattern. The yielded pseudo-boehmite peptized by HNO3, addition and gelified by evaporation in a critical concentration approximately 0.17 gcm(-3).

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The preparation of superparamagnetic magnetite (Fe(3)O(4)) nanoparticles by electro-precipitation in ethanol is proposed. Particle average size can be set from 4.4 to 9 nm with a standard deviation around 20%. Combination of wide-angle X-ray scattering (WAXS), Electron energy loss spectroscopy (EELS) and Mossbauer spectroscopy characterizations clearly identifies the particles as magnetite single-crystals (Fe(3)O(4)). (C) 2008 Elsevier B.V. All rights reserved.

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A multi-agent framework for spatial electric load forecasting, especially suited to simulate the different dynamics involved on distribution systems, is presented. The service zone is divided into several sub-zones, each subzone is considered as an independent agent identified with a corresponding load level, and their relationships with the neighbor zones are represented as development probabilities. With this setting, different kind of agents can be developed to simulate the growth pattern of the loads in distribution systems. This paper presents two different kinds of agents to simulate different situations, presenting some promissory results.

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The Ag-rich phase precipitation in the Cu-9 mass% Al was studied using differential scanning calorimetry (DSC), X-ray diffractometry (XRD) and scanning electron microscopy (SEM). The results indicated that Ag additions did not interfere on the metastable transitions sequence of the Cu-mass% Al alloy but Ag precipitation disturbs the beta phase formation reaction and the martensitic phase decomposition reaction.

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Radar and satellite data from the Tropical Rainfall Measuring Mission-Large-Scale Biosphere-Atmosphere (TRMM-LBA) project have been examined to determine causes for convective storm initiation in the southwest Amazon region. The locations and times of storm initiation were based on the National Center for Atmospheric Research (NCAR) S-band dual-polarization Doppler radar (S-Pol). Both the radar and the Geostationary Operational Environmental Satellite-8 (GOES-8) visible data were used to identify cold pools produced by convective precipitation. These data along with high-resolution topographic data were used to determine possible convective storm triggering mechanisms. The terrain elevation varied from 100 to 600 m. Tropical forests cover the area with numerous clear-cut areas used for cattle grazing and farming. This paper presents the results from 5 February 1999. A total of 315 storms were initiated within 130 km of the S-Pol radar. This day was classified as a weak monsoon regime where convection developed in response to the diurnal cycle of solar heating. Scattered shallow cumulus during the morning developed into deep convection by early afternoon. Storm initiation began about 1100 LST and peaked around 1500-1600 LST. The causes of storm initiation were classified into four categories. The most common initiation mechanism was caused by forced lifting by a gust front (GF; 36%). Forcing by terrain (>300 m) without any other triggering mechanism accounted for 21% of the initiations and colliding GFs accounted for 16%. For the remaining 27% a triggering mechanism was not identified. Examination of all days during TRMM-LBA showed that this one detailed study day was representative of many days. A conceptual model of storm initiation and evolution is presented. The results of this study should have implications for other locations when synoptic-scale forcing mechanisms are at a minimum. These results should also have implications for very short-period forecasting techniques in any location where terrain, GFs, and colliding boundaries influence storm evolution.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The objective of this work is the development of a methodology for electric load forecasting based on a neural network. Here, it is used Backpropagation algorithm with an adaptive process based on fuzzy logic. This methodology results in fast training, when compared to the conventional formulation of Backpropagation algorithm. Results are presented using data from a Brazilian Electric Company and the performance is very good for the proposal objective.